Here is restaurant data in NYC

---
title: "Dashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source_code: embed
---

```{r setup, include=FALSE}
library(flexdashboard)

library(tidyverse)
library(p8105.datasets)

library(plotly)
```


Here is restaurant data in NYC

```{r}
data(rest_inspec)

rest_inspec_mod = 
  rest_inspec %>% 
  select(dba, boro, street, cuisine_description, inspection_type, zipcode, score, grade) %>% 
  filter(
    boro == "MANHATTAN",
    inspection_type == "Cycle Inspection / Initial Inspection",
    cuisine_description %in% c("American", "French", "Irish", "Italian", "Mexican", "Turkish", "Chinese", "Indian", "Japanese", "Korean", "Latin", "Spanish", "Thai")
  ) %>% 
  distinct() %>% 
  drop_na()

```

Column {data-width=650}
-----------------------------------------------------------------------

### Chart A

```{r}
rest_inspec_scatt =
  rest_inspec_mod %>% 
  mutate(
    text_label = str_c("Cuisine_type: ", cuisine_description, "\nGrade: ", grade)
  ) %>% 
  plot_ly(
    x = ~zipcode, y = ~street, type = "scatter", mode = "markers", color = ~score, text = ~text_label, alpha = .5
    )

rest_inspec_scatt
```

Column {data-width=350}
-----------------------------------------------------------------------

### Chart B

```{r}
rest_inspec_box = 
rest_inspec_mod %>% 
  mutate(
    cuisine_description = fct_reorder(cuisine_description, score)
  ) %>% 
  plot_ly(y = ~score, color = ~cuisine_description, type = "box",
          colors = "viridis")

rest_inspec_box
```

### Chart C

```{r}
rest_inspec_bar = 
  rest_inspec_mod %>% 
  count(cuisine_description) %>% 
  mutate(cuisine_description = fct_reorder(cuisine_description, n)) %>% 
  plot_ly(x = ~cuisine_description, y = ~n, color = ~cuisine_description, type = "bar", colors = "viridis")

rest_inspec_bar
```